Mid-Level Data Analyst

Instituto de Pesquisas Eldorado

. Develop and deploy ingestion pipelines from heterogeneous sources, including REST APIs, web scraping, SQL procedures from legacy systems, and files; .

Posted 10/27/2026full-timeCampinas • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying data ingestion pipelines, implementing data transformations using PySpark and SQL, and ensuring data quality through testing and validation. Proficient in data visualization and analytics, with a strong focus on performance optimization and governance.

Highest-signal resume keywords

Data EngineeringPython/PySparkSQLDatabricksData Visualization

ATS Keywords

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Hard Skills

Data Ingestion PipelinesData TransformationsWeb ScrapingData Quality TestingRow-Level SecurityData Contract MechanismsPerformance BenchmarkingData ModelingDeclarative TransformationsUser Acceptance Testing

Soft Skills

CollaborationCommunication

Tools & Technologies

Azure Data FactoryPower BIDbtGit

Industry Keywords

Medallion ArchitectureData LineageData ClassificationAnalytical Data FormatsREST APIs

Tech Stack

Tools & technologies

AzurePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Develop and deploy ingestion pipelines from heterogeneous sources, including REST APIs, web scraping, SQL procedures from legacy systems, and files;
Support the implementation of read-only replication mechanisms for systems that do not provide direct database access, with attention to performance impact on source systems;
Implement data transformations using PySpark and SQL;
Support cost and processing performance benchmarking, contributing to the definition of more efficient sizing;
Support the development of Bronze, Silver, and Gold layers following the medallion architecture pattern;
Implement resilient web-scraping pipelines, with layout-change detection and blocking-handling mechanisms;
Support the development of the platform’s Bronze, Silver, and Gold layers, applying deduplication, normalization, and data quality testing;
Support the development of data contract mechanisms and schema drift alerts for third-party integrations;
Build dashboards and reports in Power BI from the structured data layer;
Contribute to translating business requirements into effective data models and visualizations;
Implement data access control in reports through Row-Level Security, aligned with the company’s RBAC policies;
Implement data quality tests and declarative transformations using dbt;
Support the configuration of self-service analytics features, such as Fabric Copilot;
Collaborate with the governance team to ensure proper data lineage and classification;
Diagnose and resolve performance issues in pipelines and queries;
Conduct user acceptance testing and adjust dashboards based on feedback.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or an equivalent field;
Solid experience in data engineering, with Python/PySpark and SQL;
Knowledge of Databricks (or Spark in general) and orchestration tools such as Azure Data Factory;
Knowledge of analytical data formats, including Parquet and Delta Lake;
Experience with dbt is desirable;
Knowledge of version control practices (Git) and CI/CD for data pipelines;
Experience integrating data via REST APIs;
Knowledge of data visualization best practices and data storytelling, working with diverse data sources (SQL, APIs, files, Lakehouse/Warehouse), and implementing Row-Level Security;
Willingness to travel to São Paulo is a plus;
Advanced English proficiency;
Availability to travel to Campinas and São Paulo.

Benefits

Comp & perks

Competitive compensation
Attractive benefits package
Professional development opportunities
An environment that values innovation and growth
Diverse and inclusive workplace with equal opportunities
Hybrid work